# Asymptotic unbiased density estimators

Nicolas W. Hengartner; Éric Matzner-Løber

ESAIM: Probability and Statistics (2009)

- Volume: 13, page 1-14
- ISSN: 1292-8100

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topHengartner, Nicolas W., and Matzner-Løber, Éric. "Asymptotic unbiased density estimators." ESAIM: Probability and Statistics 13 (2009): 1-14. <http://eudml.org/doc/250655>.

@article{Hengartner2009,

abstract = {
This paper introduces a computationally tractable density estimator
that has the same asymptotic variance as the classical Nadaraya-Watson
density estimator but whose asymptotic bias is zero. We achieve this result
using a two stage estimator that applies a multiplicative bias correction
to an oversmooth pilot estimator. Simulations show that our asymptotic
results are available for samples as low as n = 50, where we see an improvement of as much as 20% over the traditionnal estimator.
},

author = {Hengartner, Nicolas W., Matzner-Løber, Éric},

journal = {ESAIM: Probability and Statistics},

keywords = {Nonparametric density estimation; kernel smoother;
asymptotic normality; bias reduction; confidence intervals; nonparametric density estimation; asymptotic normality},

language = {eng},

month = {2},

pages = {1-14},

publisher = {EDP Sciences},

title = {Asymptotic unbiased density estimators},

url = {http://eudml.org/doc/250655},

volume = {13},

year = {2009},

}

TY - JOUR

AU - Hengartner, Nicolas W.

AU - Matzner-Løber, Éric

TI - Asymptotic unbiased density estimators

JO - ESAIM: Probability and Statistics

DA - 2009/2//

PB - EDP Sciences

VL - 13

SP - 1

EP - 14

AB -
This paper introduces a computationally tractable density estimator
that has the same asymptotic variance as the classical Nadaraya-Watson
density estimator but whose asymptotic bias is zero. We achieve this result
using a two stage estimator that applies a multiplicative bias correction
to an oversmooth pilot estimator. Simulations show that our asymptotic
results are available for samples as low as n = 50, where we see an improvement of as much as 20% over the traditionnal estimator.

LA - eng

KW - Nonparametric density estimation; kernel smoother;
asymptotic normality; bias reduction; confidence intervals; nonparametric density estimation; asymptotic normality

UR - http://eudml.org/doc/250655

ER -

## References

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